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Oracle 1Z0-1110-26 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Implement End-to-End Machine Learning Lifecycle | 45% | - Data preparation, exploration, and transformation - Use AutoML and built-in algorithms - Model development, training, and evaluation - Model saving, cataloging, and versioning - Deploy models and manage endpoints |
| Design and Set Up Data Science Workspace | 15% | - Configure compute shapes, storage, and networking - Manage access control, security, and IAM integration - Create and manage projects and notebook sessions |
| OCI Data Science - Introduction & Configuration | 10% | - Overview and core concepts of OCI Data Science - Tenancy and environment configuration for Data Science - Capabilities of the Accelerated Data Science (ADS) SDK |
| Integrate Related OCI Services | 10% | - Integration with OCI Object Storage, Vault, and Networking - Use OCI AI and data services with Data Science |
| Apply MLOps Practices | 20% | - Model monitoring, drift detection, and performance tracking - Governance, auditing, and compliance - ML pipelines, automation, and reproducibility |
Oracle Cloud Infrastructure Data Science Professional Sample Questions:
Which TWO statements about Oracle Cloud Infrastructure (OCI) Open Data service are true?
- A. Open Data is a dataset repository made for the people that create, use, and manipulate datasets.
- B. Audio and video formats are not available.
- C. Each dataset in Open Data consists of code and tooling usage examples for consumption and reproducibility.
- D. A primary goal of Open Data is for users to contribute to the data repositories to expand the content offered.
- E. Open Data includes text and image data repositories for AI and ML.
- F. Subscribers can pay and log into Open Data to view curated datasets that are otherwise not available to the public.
Correct Answer: A,E 🗳️
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As a data scientist, you use the Oracle Cloud Infrastructure (OCI) Language service to train custommodels. Which types of custom models can be trained?
- A. Object detection, Text classification
- B. Sentiment Analysis, Named Entity Recognition (NER)
- C. Text classification, Named Entity Recognition (NER)
- D. Image classification, Named Entity Recognition (NER)
Correct Answer: C 🗳️
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You have just started as a data scientist at a healthcare company. You have been asked to analyze and improve a deep neural network model, which was built based on the electrocardiogram records of patients. There are no details about the model framework that was built. What would be the best way to find more details about the machine learning models inside the model catalog?
- A. Check for metadata tags
- B. Check for model taxonomy details
- C. Refer to the code inside the model
- D. Check for provenance details
Correct Answer: D 🗳️
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What is the primary difference between a data scientist and a data engineer?
- A. A data engineer builds data pipelines and helps prepare data, while a data scientist is responsible for data collection, preparation, and analysis.
- B. A data engineer creates data flows to be used as templates by the data analyst.
- C. A data engineer collects and prepares data, and a data scientist then analyzes it.
- D. A data engineer analyzes data after a data scientist collects and prepares it.
Correct Answer: C 🗳️
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You have just completed analyzing a set of images by using Oracle Cloud Infrastructure (OCI) Data Labeling, and you want to export the annotated dat a. Which TWO formats are supported?
- A. CONLL V2003
- B. Data Labeling Service Proprietary JSON
- C. Spacy
- D. COCO
Correct Answer: B,D 🗳️
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